Remote Sensing of Atmospheric Conditions for Wind Energy Applications

Abstract

"Wind energy is the renewable energy source that contributes the most to the electricity generation worldwide. The need to further understand and efficiently use available wind resources is the key motivation for research in wind energy. The levelized cost of energy from wind power is competitive with that of the conventional energy sources at wind-favorable land sites, while efforts are made to lower the cost of wind energy at offshore, complex, and forested areas. The wake effect within and between wind farms and wind-power forecasting are areas with increasing importance because of the need to accurately predict wind power. There is, therefore, a need for reliable, robust, and accurate measurements and datasets to further improve our understanding of the physical conditions in which wind turbines and wind farms operate and for flow model evaluation.

Nowadays, remote sensing observations are used widely in wind energy applications. During the last couple of years, remote sensing technologies for wind have been improved, both in terms of accuracy and costs. Combined measurement infrastructures, such as that of WindScanner.eu, and new advancements for the measurement of atmospheric turbulence and the wind turbine power performance, turbine wakes, and for improvement of the turbine control, are being progressively achieved. Commercial acceptance of lidars, including floating/buoy lidars, for wind resource assessment, is also on-going. Based on airborne lidar, high-resolution land surface maps are retrieved in forested and complex terrain and provide new valuable inputs to micro- and meso-scale modeling. Surface roughness, terrain elevation, albedo, vegetation parameters, and land- and sea surface temperatures are assessed based on Earth Observation (EO) data and used as input for flow modeling of wind resources (wind atlas) and for the forecasting of wind power at short temporal scales. EO microwave data are used for offshore wind field mapping and applied for wind resource estimation, wind park wake effect, and long-term wind climate conditions."